Computational Aesthetics and Identification of Working Style

Tänapäeval kasutab meeletu hulk ettevõtteid protsessimudelitel põhinevate äriprotsesside haldamiseks, teostamiseks, monitoorimiseks ja analüüsimiseks protsessiteadlikke infosüsteeme. Lisaks genereerivad need tarkvarasüsteemid monitoorimisetapi osana ka sündmuste logisid, mis kujutavad endast tegelikku faktidest tuletatud (aposteriori) töövoogu ning neid analüüsitakse protsessiandmete hankimise tehnikate abil. Selles töös, osana protsessiandmete hankimisest, tutvustame tööstiili kontseptsiooni töö olemuse kõikehõlmava analüüsi tööriistana. Äriprotsesse ja komponentidevahelist vastastikust sõltuvust saab hinnata tööstiili perspektiivist, mis väljendub meetmetes ja mustrites. Defineerime uuendusliku sündmuste logi esitlemise lähenemise, kus logifaili käsitletakse kujutisena. Lisaks pakume välja meetmete arvutamise ja mustrite identifitseerimise algoritmid, mis põhinevad kujutiste analüüsitehnika ja arvutusesteetika kombinatsioonil. Selle tulemusena on loodud tööstiili hindamise veebipõhise rakenduse prototüüp.Nowadays, an enormous amount of companies use Process-Aware Information Systems to manage, perform, monitor and analyze business processes based on process models. Moreover, as a part of the monitoring stage, these software systems generate event logs, which represent actual a-posteriori workflow and are analyzed by process mining techniques. In this work, as a part of process mining, we introduce the concept of working style as the tool for comprehensive analysis of the nature of work. Business processes and interdependencies between its constituents can be evaluated from the perspective of working style which is represented by measures and patterns. We define the novel event log representation approach, where the log file is treated as an image. Additionally, we propose measure computation and pattern identification algorithms based on image analysis technique in combination with computational aesthetics. As a result, the web-based prototype application for working style evaluation has been built

Rational Beauty in Computational Aesthetics

Given AI's growing importance, it has always been a hot topic in academic circles, with the main opposing views consisting of positive and negative sides. However, the debate on "unique human creativity," such as art, will be particularly heated. Some believe that AI will usher in a new art genre and a new way of creating, while others believe that AI's works of art will never be able to compete with those of humans. In this study, the artistic creation and evaluation of AI in computational aesthetics will be analyzed and discussed, but the discussion will not be limited to computational aesthetics alone. The creative creation analysis of AI can be traced back to the summit of beauty itself to express support for computational aesthetics and AI artistic creation

Artificial life meets computational creativity?

I review the history of work in Artificial Life on the problem of the open-ended evolutionary growth of complexity in computational worlds. This is then put into the context of evolutionary epistemology and human creativity

COMPUTATIONAL MODELLING OF HUMAN AESTHETIC PREFERENCES IN THE VISUAL DOMAIN: A BRAIN-INSPIRED APPROACH

Following the rise of neuroaesthetics as a research domain, computational aesthetics has also known a regain in popularity over the past decade with many works using novel computer vision and machine learning techniques to evaluate the aesthetic value of visual information. This thesis presents a new approach where low-level features inspired from the human visual system are extracted from images to train a machine learning-based system to classify visual information depending on its aesthetics, regardless of the type of visual media. Extensive tests are developed to highlight strengths and weaknesses of such low-level features while establishing good practices in the domain of study of computational aesthetics. The aesthetic classification system is not only tested on the most widely used dataset of photographs, called AVA, on which it is trained initially, but also on other photographic datasets to evaluate the robustness of the learnt aesthetic preferences over other rating communities. The system is then assessed in terms of aesthetic classification on other types of visual media to investigate whether the learnt aesthetic preferences represent photography rules or more general aesthetic rules. The skill transfer from aesthetic classification of photos to videos demonstrates a satisfying correct classification rate of videos without any prior training on the test set created by Tzelepis et al. Moreover, the initial photograph classifier can also be used on feature films to investigate the classifier’s learnt visual preferences, due to films providing a large number of frames easily labellable. The study on aesthetic classification of videos concludes with a case study on the work by an online content creator. The classifier recognised a significantly greater percentage of aesthetically high frames in videos filmed in studios than on-the-go. The results obtained across datasets containing videos of diverse natures manifest the extent of the system’s aesthetic knowledge. To conclude, the evolution of low-level visual features is studied in popular culture such as in paintings and brand logos. The work attempts to link aesthetic preferences during contemplation tasks such as aesthetic rating of photographs with preferred low-level visual features in art creation. It questions whether favoured visual features usage varies over the life of a painter, implicitly showing a relationship with artistic expertise. Findings display significant changes in use of universally preferred features over influential vi abstract painters’ careers such an increase in cardinal lines and the colour blue; changes that were not observed in landscape painters. Regarding brand logos, only a few features evolved in a significant manner, most of them being colour-related features. Despite the incredible amount of data available online, phenomena developing over an entire life are still complicated to study. These computational experiments show that simple approaches focusing on the fundamentals instead of high-level measures allow to analyse artists’ visual preferences, as well as extract a community’s visual preferences from photos or videos while limiting impact from cultural and personal experiences

The Enigma of Complexity

In this paper we examine the concept of complexity as itapplies to generative art and design. Complexity has many different, dis-cipline specific definitions, such as complexity in physical systems (en-tropy), algorithmic measures of information complexity and the field of“complex systems”. We apply a series of different complexity measuresto three different generative art datasets and look at the correlationsbetween complexity and individual aesthetic judgement by the artist (inthe case of two datasets) or the physically measured complexity of 3Dforms. Our results show that the degree of correlation is different for eachset and measure, indicating that there is no overall “better” measure.However, specific measures do perform well on individual datasets, indi-cating that careful choice can increase the value of using such measures.We conclude by discussing the value of direct measures in generative andevolutionary art, reinforcing recent findings from neuroimaging and psy-chology which suggest human aesthetic judgement is informed by manyextrinsic factors beyond the measurable properties of the object beingjudged

Digital aesthetics: the discrete and the continuous

Aesthetic investigations of computation are stuck in an impasse, caused by the difficulty of accounting for the ontological discrepancy between the continuity of sensation and the discreteness of digital technology. This article proposes a theoretical position intended to overcome that deadlock. It highlights how an ontological focus on continuity has entered media studies via readings of Deleuze, which attempt to build a ‘digital aisthesis’ (that is, a theory of digital sensation) by ascribing a ‘virtuality’ to computation. This underpins, in part, the affective turn in digital theory. In contrast to such positions, this article argues for a reconceptualization of formal abstraction in computation, in order to find, within the discreteness of computational formalisms (and not via the coupling of the latter with virtual sensation), an indeterminacy that would make computing aesthetic qua inherently generative. This indeterminacy, it is argued here, can be found by reconsidering, philosophically, Turing’s notion of ‘incomputability’

Book review: how to be a geek: essays on the culture of software by Matthew Fuller

In How to be a Geek: Essays on the Culture of Software, Matthew Fuller explores the bits and bytes that have reshaped our world through a collection of essays that examines the figure of the geek and software cultures. While the lack of cohesive thread and use of terminology means this collection is best suited to scholars already familiar with the field rather than newcomers, the book contains some useful and astute insights, writes Wendy Liu

Modelling the underlying principles of human aesthetic preference in evolutionary art

Our understanding of creativity is limited, yet there is substantial research trying to mimic human creativity in artificial systems and in particular to produce systems that automatically evolve art appreciated by humans. We propose here to study human visual preference through observation of nearly 500 user sessions with a simple evolutionary art system. The progress of a set of aesthetic measures throughout each interactive user session is monitored and subsequently mimicked by automatic evolution in an attempt to produce an image to the liking of the human user

At the Limits of Species Being: Sensing the Anthropocene

Autonomous Marxism has generated a lexicon for responding to transformations in human labor, particularly around the role of technological development. Autonomists have mapped how the conditions of post-Fordism have put elements of the mind, sociability, virtuosity—or “the soul” in Franco Berardi's terms—to work. But that labor, in accordance with capitalist valorization, is nearly always human. At best, it is human labor supplemented with machines. But what are we to make of the lively materials—of human and nonhuman provenance alike—now at “work” alongside us? This essay takes up this question in an analysis of the field of biosensing. It explores Marx's concepts of species being and the general intellect to reconsider what can be said of “living labor” and its potential at a time when nonhuman life is increasingly a central component of production. It suggests that alongside the so-called Anthropocene, biosensing marks a redistribution of both the work and the precarity associated with our mode of production. While the field forges engagements with nonhuman others and a growing awareness of planetary life, it also operates according to an imaginary of planetary management, the possibility of producing for a collective health and the “whole of nature.